ObjectiveTo explore the possible mechanism of Jianpi Huazhuo Tiaozhi Granule （健脾化浊调脂颗粒， JHTG） in treating atherosclerosis （AS） based on the regulation of perivascular adipose tissue （PVAT） browning via the phosphoinositide 3-kinase/protein kinase B （PI3K/AKT） signaling pathway. MethodsFifteen SPF male C57BL/6J mice served as control group， while 76 ApoE^-/- mice were first fed a high-fat diet for 16 weeks to establish AS model. After successful modeling， they were randomly divided into model group （n=16）， as well as the browning group， the low-， medium- and high-dose JHTG group， with 15 mice in each group. The browning group was intraperitoneally injected with β3-adrenergic receptor agonist CL 316243 at 1 mg/（kg·d） once daily. The low-， medium- and high-dose JHTG groups were treated with 4.3 g/（kg·d）， 8.6 g/（kg·d）， and 17.2 g/（kg·d） of JHTG by gavage， respectively， while the control group and the model group were given normal saline at 10 ml/（kg·d） by intragastric administration， once daily. All groups received continuous intervention for 4 weeks. The aorta was collected to assess the plaque ratio by gross oil red O staining. HE staining was used to measure the plaque area in cross-sections. Masson staining was employed to detect the proportion of collagen fibers in plaque. Transmission electron microscopy was used to observe the quantity and morphological changes of mitochondria and lipid droplets in adipocytes. The levels of serum triglycerides （TG）， total cholesterol （TC）， high-density lipoprotein cholesterol （HDL-C）， and low-density lipoprotein cholesterol （LDL-C） were detected， as well as tumor necrosis factor α （TNF-α） and interleukin 6 （IL-6） levels in the PVAT and aorta. The protein levels of adiponectin and leptin in PVAT， and protein expression levels of phosphoinositide 3-kinase （PI3K）， phosphorylated phosphoinositide 3-kinase （p-PI3K）， protein kinase B （AKT）， phosphorylated protein kinase B （p-AKT）， uncoupling protein 1 （UCP1）， peroxisome proliferator-activated receptor γ coactivator 1α （PGC-1α）， and PR domain containing 16 （PRDM16） were measured. The mRNA expression levels of UCP1， PGC-1α and PRDM16 in PVAT were detected. ResultsCompared to the control group， the model group showed increased serum TG， TC， and LDL-C levels and decreased HDL-C level， elevated TNF-α and IL-6 levels in PVAT and aorta， decreased average fluorescence intensity of adiponectin， increased average fluorescence intensity of leptin， reduced p-PI3K/PI3K and p-AKT/AKT values as well as protein levels and mRNA expression levels of UCP1， PGC-1α and PRDM16 （P＜0.01）. The pathological results showed that no significant plaque formation was observed in the aortas of mice in the control group. In the model group， multiple plaques were observed in the aortas， with large numbers of foam cells， cholesterol crystals， and inflammatory cell aggregation in the plaques. Compared to the model group， the browning group and the high-dose JHTG group significantly improved the above indicators and aortic pathological changes （P＜0.05 or P＜0.01）. Three JHTG groups showed a dose-dependent effect in reducing LDL-C level and plaque ratio by gross oil red O staining， elevating the average fluorescence intensity of adiponectin， the p-AKT/AKT value， the protein level of PGC-1α， and the mRNA expression levels of UCP1 and PRDM16 （P＜0.05）. The high-dose JHTG group and the browning group showed similar efficacy in improving the pathology of the aorta. ConclusionJHTG may promote PVAT browning in AS model mice through the PI3K/AKT pathway， improve the endocrine function of PVAT， inhibit aortic inflammation， and thereby ameliorate the formation of AS plaques.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

ObjectiveThis study aimed to evaluate the effectiveness of various statistical methods based on the complementary sensitivity analysis framework recommended by the European Medicines Agency (EMA) in Alzheimer’s disease clinical trials, providing a reference for statistical practice that meets international regulatory standards for similar studies. MethodsBased on longitudinal data from a phase Ⅲ clinical trial for the treatment of Alzheimer’s disease, the change from baseline in Alzheimer’s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) score from baseline at week 26 (with a decrease indicating cognitive improvement) was used as the primary outcome measure. This study employed a mixed-effects model with repeated measures (MMRM) under the assumption of missing at random (MAR) as the primary analysis, while using critical point analysis, rank-based analysis, and slope-based analysis for sensitivity verification. A systematic comparison of the efficacy estimation results from the four analytical methods was conducted to compare the consistency and robustness differences in research conclusions across different analytical strategies. ResultsThe primary analysis results from the MMRM showed that the improvement in ADAS-Cog score from baseline at week 26 in the treatment group was superior to that in the placebo group (LSMD=-3.22, 95%CI: -4.55 to -1.88, P<0.001). Both rank-based analyses and slope-based analyses indicated significant differences between groups (both P<0.001). Critical point analyses revealed that the treatment effect was negative under most reasonable missing hypothesis scenarios, with the effect value only potentially turning positive in extreme non-random missing scenarios. There was no overall reversal of the efficacy conclusion. ConclusionThe combination of MMRM, critical point analysis, rank-based analysis, and slope-based analysis can effectively address the challenge of missing data in clinical trials for progressive diseases. This strategy fully complies with international regulatory standards, verifies efficacy conclusions from multiple perspectives, and enhances the credibility and scientific validity of clinical trial results. It can provide a practical reference for statistical analysis of missing data in similar clinical trials for progressive diseases.

Objective: To analyze changes in Rh system antibodies among antibody-positive patients and evaluate the efficacy of Rh phenotype-matched electronic cross-matching (hereinafter referred to as Rh-ECM). Methods: A retrospective analysis was performed on antibody screening data of 48 254 patients in our hospital from December 2023 to March 2025. The antibody screening results were compared between the pre-application phase (n=46 346, control group) and post-application phase (n=48 254, experimental group) of Rh-ECM technology, focusing on the changes in the proportion of Rh system antibodies, with statistical analysis conducted using SPSS 26.0 software. Meanwhile, the initial and re-examination situations of Rh antibody in the antibody screening of approximately 20 000 person-times each before (June 2019 to June 2020, n=21 048) and after (July 2020 to April 2021, n=20 965) of Rh-ECM were evaluated to explore the influence of Rh-ECM on the detection rate of Rh antibody. Results: After Rh-ECM implementation, 345 positive cases (0.7%) (345/48 254) were detected among 48 254 patients, primarily consisting of mns system antibodies (128 cases, 37.1%) (128/345) and rh system antibodies (95 cases, 27.5%) (95/345). Before Rh-ECM implementation, 199 positive cases (0.4%) (199/46 346) were detected among 46 346 patients, with rh system antibodies accounting for 97 cases (48.7%) (97/199). The difference in the composition ratio of Rh antibodies between the two phases was statistically significant (P<0.001), and the relative risk ratio of Rh antibody detection after Rh-ECM implementation was 56.5% compared to before. Another set of data analysis showed that before Rh-ECM, there were 37 cases with initial positive results and 8 cases with re-examination positive results; after Rh-ECM, these numbers were 44 and 2 respectively There was a statistically significant difference in the re-examination positive rate of Rh antibodies between the two stages (P<0.05). Conclusion: The implementation of Rh-ECM technology significantly reduced the proportion of Rh system antibodies among patients with positive antibody screening results. This suggests that Rh-ECM can effectively reduce the detection rate of Rh antibodies, which may be related to the reduced risk of antibody production due to Rh-matched transfusion, thus improving transfusion safety. Therefore, Rh-ECM is worthy of broader promotion in clinical transfusion testing.

Obesity, as a chronic recurrent disease, has become a major public health challenge in China. To implement the requirements of the Healthy China Initiative (2019—2030), under domestic guidelines or consensus statements on overweight and obesity, and in alignment with the latest scientific advances globally, the Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition) was developed. This protocol was drafted by the Health Management Center of Shanghai Changzheng Hospital and formulated through multiple rounds of deliberation by experts in China’s health examination quality control field. The protocol establishes unified standards for screening facilities, personnel qualifications, and measurement or testing procedures. It defines specific screening items, outlines a standardized screening pathway, and sets requirements for the final medical review, ensuring the scientific validity, effectiveness, and safety of the screening process. The implementation of this protocol will enhance the consistency of weight management practices for adults across health examination institutions and strengthen the quality control of overweight and obesity screening programs.

Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.

Filamenting temperature-sensitive mutant Z (FtsZ), a protein essential for bacterial cell division, is highly conserved across bacterial species but absent in humans, positioning it as a strategic target for the development of antibiotics. Significant efforts to identify FtsZ inhibitors-via biochemical assays (e.g., GTPase activity) and cellular approaches (e.g., immunofluorescence)-have yielded over 100 natural products and synthetic compounds, whose cheminformatics clustering underscores a limited chemical diversity among the current scaffolds. Structural studies, including X-ray crystallography and cryo-electron microscopy, have resolved 97 FtsZ structures revealing conserved polymerization mechanisms and conformational plasticity, as exemplified by extremophile adaptations (e.g., Shewanella benthica from the high-pressure environment of the Mariana Trench's Challenger Deep). However, clinical translation is hindered by weak binding affinities, inhibitory inefficacy, dynamic conformational flexibility, and evolving drug resistance linked to FtsZ's functional plasticity. To address these challenges, future efforts should be directed to resolve transient assembly intermediates, leveraging machine learning with high-throughput screening, and integrating structural biology with pharmacokinetic optimization. Multidisciplinary strategies combining these approaches hold promise for translating FtsZ-focused research into clinically viable therapies, addressing the critical unmet need posed by antibiotics resistance.

The translation of genetic findings from genome-wide association studies into actionable therapeutics persists as a critical challenge in Alzheimer's disease (AD) research. Here, we present PI4AD, a computational medicine framework that integrates multi-omics data, systems biology, and artificial neural networks for therapeutic discovery. This framework leverages multi-omic and network evidence to deliver three core functionalities: clinical target prioritisation; self-organising prioritisation map construction, distinguishing AD-specific targets from those linked to neuropsychiatric disorders; and pathway crosstalk-informed therapeutic discovery. PI4AD successfully recovers clinically validated targets like APP and ESR1, confirming its prioritisation efficacy. Its artificial neural network component identifies disease-specific molecular signatures, while pathway crosstalk analysis reveals critical nodal genes (e.g., HRAS and MAPK1), drug repurposing candidates, and clinically relevant network modules. By validating targets, elucidating disease-specific therapeutic potentials, and exploring crosstalk mechanisms, PI4AD bridges genetic insights with pathway-level biology, establishing a systems genetics foundation for rational therapeutic development. Importantly, its emphasis on Ras-centred pathways-implicated in synaptic dysfunction and neuroinflammation-provides a strategy to disrupt AD progression, complementing conventional amyloid/tau-focused paradigms, with the future potential to redefine treatment strategies in conjunction with mRNA therapeutics and thereby advance translational medicine in neurodegeneration.

Bombesin receptor subtype-3 (BRS3) is an orphan G protein-coupled receptor (GPCR) that plays critical roles in energy homeostasis, glucose metabolism, and insulin secretion. Recent structural studies have elucidated BRS3 signaling mechanisms using synthetic ligands, including BA1 and MK-5046. However, the molecular basis of BRS3 activation by bioactive natural compounds and their derivatives, particularly those derived from traditional Chinese medicine, remains unclear. Here, we present high-resolution cryogenic electron microscopy (cryo-EM) structures of the human BRS3-G_q complex in both unliganded and active states bound by two herb-derived compounds (DSO-5a and oridonin), at resolutions of 2.9, 2.8, and 2.9 Å, respectively. These structures display distinct ligand recognition patterns between DSO-5a and oridonin. Although both compounds bind to the orthosteric pocket, they differentially engage the interaction network of BRS3, as demonstrated by mutagenesis studies assessing calcium mobilization and inositol phosphate 1 (IP1) accumulation. These findings enhance our understanding of BRS3 activation and provide valuable insights into the development of small-molecule BRS3 modulators with therapeutic potential.